Maternal Diabetes and Overweight and Congenital Heart Defects in Offspring

This cohort study investigates the association of maternal diabetes and body mass index with congenital heart defects in offspring.


Introduction
Congenital heart defects (CHDs) are the most common congenital malformations in children, traditionally thought to occur in approximately 1 in 100 newborns. 1Together with prematurity and birth asphyxia and trauma, CHDs are among the leading causes of deaths in the first year of life in high-resource settings. 2][8][9][10] The role of maternal type 1 diabetes (T1D) as a significant risk factor has been well documented, but the significance of GD and maternal obesity and overweight is less clear, especially for specific CHD subgroups.
Moreover, to our knowledge, there are no large studies investigating maternal diabetes and obesity in the same model.Given that these conditions often occur in parallel, better understanding of the contribution of each factor to offspring risk for CHD in general and for specific CHD subgroups may not only aid prevention, but also provide cues to direct future research in unraveling underlying molecular-level mechanisms.We investigated the association of maternal PGD, GD, and overweight and obesity with the risk of isolated CHDs and CHDs of selected subgroups in a nationwide register study from Finland.

Methods
This cohort study was approved by the Research Ethics board of the Finnish Institute for Health and Welfare and relevant register authorities.No informed consent from registered persons is required for the use of pseudonymized register data for research purposes in Finland.The reporting of the study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Study Design and Setting
We conducted a nationwide register study in Finland including all children born (liveborn and stillborn) in 2006 to 2016 and their mothers (eFigure 1 in Supplement 1).Exclusion criteria included missing information on gestational age, unclear CHD diagnosis, and diagnosis for syndromes, chromosomal aberrations, or extracardiac malformations (major anomalies according to EUROCAT) 11 (eFigure 1 and eTable 1 in Supplement 1).

Data Sources
Data were collected from the following national registers: the Medical Birth Register (MBR), Register of Congenital Malformations (RCM), and Care Register for Health Care (CRHC) maintained by the Finnish Institute for Health and Welfare and the Register of Special Reimbursements for Prescription Medicines maintained by the Social Insurance Institution of Finland. 12,13Every Finnish citizen and permanent resident has a personal identification number, which enables linkage of information between registers.Information on maternal and paternal education was received from Statistics Finland.A detailed description of these registers is provided in the eMethods in Supplement 1.

Outcomes
The main outcome was isolated CHD in the child obtained from the RCM.Isolated CHD was defined as having a diagnosis for 1 or more CHDs and not having diagnoses for chromosomal aberrations, syndromes, or any other major extracardiac anomaly (eTable 1 in Supplement 1).Isolated CHDs were divided into 9 groups according to their anatomical origin: atrial septal defects, ventricular septal defects (VSD), other septal defects, transposition of great arteries, left ventricular outflow tract
The complex group included rare severe diagnoses, such as isomerisms, double outlet left ventricle, double inlet left ventricle, and some complex combined defects.

Exposures and Covariates
Maternal body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) was calculated from the weight and height reported in the MBR.Height was self-reported.
Prepregnancy weight is self-reported during the first antenatal clinic visit, when weight is also measured.BMI was categorized as underweight (<18.5),normal (18.5-24.9),overweight (25.0-29.9),and obese (Ն30.0).Maternal diabetes was classified as no diabetes, T1D, type 2 or other diabetes (T2D), and GD according to information in the MBR, CRHC, and Register of Special Reimbursements for Prescription Medicines (eMethods and eTable 3 in Supplement 1).
Covariates considered as potential confounders included year of birth, maternal age, parity, maternal smoking during pregnancy (yes or no), and highest parental education level, obtained from MBR and Statistics Finland.Data on highest parental completed education during the study period were categorized according to the International Standard Classification of Education 2011 (ISCED) as low (ISCED classes 0-2), intermediate (ISCED classes 3-5), high (ISCED classes 6-8), or missing. 14

Statistical Analysis
Categorical variables were reported as frequencies and percentages and continuous variables as means and SDs.First, logistic regression adjusted for child birth year was used for analyzing the association of maternal BMI classes with isolated CHDs and selected CHD subgroups in offspring.
Similarly, logistic regression analysis adjusted for child birth year was used for analyzing the association of maternal diabetes with isolated CHDs and the same CHD subgroups.
Then, multivariable logistic regression analysis was used to analyze the association of maternal diabetes and BMI with isolated CHDs and selected CHD subgroups in offspring, and the model was adjusted for the previously mentioned covariates.Diabetes and BMI were assessed in the same analysis given that the conditions often occur in parallel.Finally, multiplicative interaction of maternal diabetes and BMI with isolated CHDs and CHD subgroups was analyzed using logistic regression analysis, first by adjusting for child birth year and then adjusted for the previously mentioned covariates.
Results of logistic regression are presented as odds ratios (ORs) with 95% CIs as measures of associations.Individuals with missing data were excluded from the multivariable logistic regression analysis.The comparison of isolated CHD frequencies between individuals with missing and those with nonmissing data was made with the χ 2 test.
Population-attributable risk was calculated using an indirect method standardized by maternal age to analyze the risk for isolated CHDs in members of the total population that is attributable to risk factors, which were maternal diabetes and obesity.The attributable risk was calculated to analyze the proportion of isolated CHDs in children exposed to maternal diabetes or obesity.
Analyses were performed in January 2022 until November 2023.We considered 2-sided P values less than .05statistically significant.Data handling and analyses were performed using SAS Enterprise Guide statistical software versions 7.1 and 8.3 (SAS Institute).

CHD Subgroup Analyses
The logistic regression analysis with offspring CHD subgroups as outcomes and adjusted for birth year is presented in Figure 2 and eFigure 4 in Supplement 1.After models were adjusted for other covariates (Figure 3; eFigure 5 in Supplement 1), T1D was associated with the greatest increase in risk for transposition of great arteries (OR, 7.

Attributable and Population-Attributable Risk
We determined the attributable risk and population-attributable risk with overweight or obesity and diabetes associated with CHD in offspring (

Missing Data
Data were missing on maternal smoking status during pregnancy in 14 845 individuals (2.4%), maternal BMI in 12 454 individuals (2.0%), and highest parental education level in 29 536 individuals (4.8%).There were no differences in outcomes for individuals with missing and nonmissing data in the study population (eTable 6 in Supplement 1).

Discussion
This nationwide register cohort study quantified the increase in risk of offspring CHDs that was associated with maternal diabetes and overweight or obesity in pregnancy.While maternal T1D was associated with the greatest increase risk, with 3.77-fold increased odds for any CHD and an association with increased risk in most CHD subcategories, maternal overweight and obesity were

<.001
The analysis of the association of maternal body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and diabetes with offspring CHD subgroup was adjusted by birth year of the child.Normal BMI (18.5-24.9)and no diabetes were used as reference groups.Statistical significance was reached with P <. 05.Factors with NA could not be analyzed owing to low population numbers.ASD indicates atrium septal defect; GD, gestational diabetes; LVOTO, left ventricle outflow tract obstruction; NA, not applicable; OR, odds ratio; RVOTO, right ventricle outflow tract obstruction; T1D, type 1 diabetes; T2D, type 2 diabetes or other diabetes; TGA, transposition of great arteries; VSD, ventricular septal defect.associated with increased risk for only complex defects and outflow tract obstruction defects.Intriguingly, maternal overweight was associated with lower odds of VSD in offspring.Furthermore, there was no interaction of maternal diabetes and BMI in the association with isolated CHD, suggesting that both were individual risk factors associated with the outcome.These results may suggest that maternal diabetes and overweight or obesity have distinct teratogenic mechanisms given that associated changes in odds were different for many CHD subgroups, and in some cases even opposite..87

<.001
The multivariable logistic regression analysis of the association of maternal body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and diabetes with CHD subgroups was adjusted to maternal smoking, maternal age, birth year of the child, first parity, and highest parental education level.Normal BMI (18.5-24.9)and no diabetes were used as reference groups.Statistical significance was reached with P < .05.Factors with NA could not be analyzed owing to low population numbers.ASD indicates atrium septal defect; GD, gestational diabetes; LVOTO, left ventricle outflow tract obstruction; NA, not applicable; OR, odds ratio; RVOTO, right ventricle outflow tract obstruction; T1D, type 1 diabetes; T2D, type 2 diabetes or other diabetes; TGA, transposition of great arteries; VSD, ventricular septal defect.a Any diabetes includes GD, T1D, and T2D.
In general, our study indicated that maternal overweight and obesity were associated with smaller increases in CHD odds in offspring than previously reported.We speculate that this may be due to our comprehensive data on maternal diabetes, which likely accounts for a larger part of the risk in individuals with overweight and obesity than previously thought.This is in line with a recent smaller study from China 15 showing that PGD partially mediated the association between maternal obesity and CHD.In our study, maternal overweight and obesity were associated with an increased risk for complex defects and outflow tract obstruction defects, whereas 2 large previous studies found associations with a wider range of defects and with higher ORs. 6,8These studies, however, did Although the authors adjusted analyses for GD, the prevalence of GD was 6.3% in mothers of offspring with CHDs and 4.3% in those in the control group, and thus GD was potentially underreported.In our study, GD occurred frequently with BMI in mothers of children with CHDs.
However, there was no interaction between maternal diabetes and BMI in the association with isolated CHDs in general, and a small interaction association was observed for LVOTO defects.Thus, it is likely that previous studies underestimated the role of maternal diabetes in their analyses.
In several smaller studies showing no association between maternal BMI and offspring CHDs or an association with some increase in risk of CHDs, findings on the association with specific CHD subtypes were inconsistent.Interestingly, our results indicated a lower risk for VSD in offspring of mothers with overweight, while previous reports have shown no association 8 or an increased risk. 7Maternal obesity has been shown to be associated with increased birth weight in offspring 21,22 and increased left ventricle 23 and interventricular septum 24 thickness during infancy.Thus, one explanation could be that increased septum thickness in these infants may contribute to the closure of small muscular defects before they are diagnosed.However, maternal T1D is also known to be associated with ventricular hypertrophy in offspring in the neonatal period, 25 but unlike maternal overweight, it is also associated with an increased risk for offspring VSD, as shown by us and others.This suggests that whereas T1D is associated with abnormal cardiac septation, maternal overweight and obesity are not, pointing to different teratogenic mechanisms in these 2 conditions.However, it should be noted that the true prevalence of isolated VSD is difficult to estimate, which could have had an impact on the specific assessment of the association of investigated risk factors with isolated VSD. 26,27e association of maternal T1D with offspring risk for CHDs is well known.In line with previous studies, 9,[28][29][30] our results demonstrated a 3-to 4-fold increased risk for any CHD, and the risk was increased for all CHD subgroups that had enough individuals to determine it.GD was associated with increased risk for any CHD and LVOTO defects in the logistic regression adjusted for child birth year; however, there were no associations for these outcomes in the multivariable analysis.Given that GD is highly prevalent, occurring in 1 in 3 expectant mothers, any risk increase is important at the population level.This was demonstrated by a population-attributable risk of 1.23% for GD compared with 1.93% for T1D, which is considerably less prevalent.
During the 2006 to 2016 study period, the screening policy of GD in Finland was changed from risk factor based to comprehensive screening, introduced by a 2008 guideline.This resulted in an increased number of women screened and milder cases included as GD with less severe mean perinatal and neonatal outcomes. 31,32In addition, the proportion of parturient individuals who were JAMA Network Open | Pediatrics obese and older (aged Ն35 years) increased during the study period, 33 which may also be associated with the increase in GD prevalence.These changes were also likely to affect the association found between diagnosed GD and CHDs.
Higher plasma glucose values during early pregnancy have been associated with an increased risk for CHDs in offspring in mothers without diabetes, 34 and hyperglycemia is likely the major teratogenic factor in T1D. 35,36The pathophysiological processes behind GD and obesity-associated risk are less well known.It is not unreasonable to speculate that at least some mothers diagnosed with GD later in pregnancy have glycemic dysregulation and pathologically high glucose values already in early pregnancy; however, additional mechanisms should be considered.Studies from 2015 to 2020 [37][38][39] have demonstrated distinct early pregnancy metabolomic profiles, including exaggerated dyslipidemia and increased inflammatory markers in mothers who later developed GD.
Abnormal early pregnancy maternal lipid profiles have been associated with increased risk for CHDs in offspring. 40,413][44] These findings suggest that obesity and GD-mediated abnormal metabolomics related to inflammation, oxidative stress, and hyperlipidemia could be associated with an additive risk in individuals who are genetically predisposed.The association of maternal overweight and obesity with risk of offspring LVOTO, RVOTO, and complex defects warrants further mechanistic research on these CHD subtypes to identify potentially modifiable pathophysiological processes.
The strengths of this study include using nationwide register data with an unselected population of all children born in 2006 to 2016 in Finland.The data on exposures and outcomes were prospectively collected and comprehensively and reliably defined.Maternal diabetes was defined based on 3 unrelated registers, and we assessed associations of PGD and GD separately.In addition, we were able to assess the severity of obesity.For the analysis, we included only individuals with isolated heart defects without syndromes or any other major malformations, leading to exclusion of most individuals with definitive or probable larger structural genetic defects with likely different etiologies.

Limitations
This study has several limitations.To our knowledge, it is thus far the largest population-based study to address the combined association of diabetes and obesity with offspring risk for CHDs.Although we used a national, 11-year cohort, the number of individuals in CHD subgroups remained limited, which was seen as large CIs in many significant findings.Another important limitation was that the data on pregnancy terminations and miscarriages were not reliably available.Congenital anomalies are known to be common in miscarriages, and approximately 350 pregnancy terminations are made annually due to major congenital anomalies in Finland.It is likely that some associations were missed because we did not have these data, and future studies including pregnancy terminations and stillbirths before 22 gestational weeks would be important.Additionally, health care database data (particularly self-reported measures, such as height and weight used for determining BMI) are not always 100% accurate, and it is possible that these led to some inaccuracies in results.

Conclusions
This cohort study emphasizes T1D as a risk factor associated with offspring CHDs, whereas GD and maternal overweight and obesity were associated with a smaller increase in risk, at least in this highresource setting with universal antenatal care.However, with increasing prevalence of GD and maternal overweight, the risk at the population level is substantial.It has been shown that standard treatment of maternal diabetes is associated with reduced risk of anatomical malformations in offspring. 45Thus, primary prevention of maternal overweight and obesity and careful treatment of PGD may hold the opportunity to reduce the burden of disease.Finally, a better understanding of the

Figure
Figure 2. Association Between Maternal Factors and Congenital Heart Defect (CHD) Subgroups

Figure
Figure 3. Association Between Maternal Factors and Congenital Heart Disease (CHD) Subgroups in Multivariable Analysis not adjust for maternal diabetes comprehensively.The study by Persson et al 8 on 28 628 individuals with CHDs and 2 050 491 individuals without CHDs excluded those with PGD from the analysis and lacked GD as a covariate in the multivariate model.The study by Madsen et al, 6 including 11 263 individuals with CHDs and 140 470 individuals in the control group, presented no information on T1D.
).The attributable risk of diabetes was 17.20% (95% CI, 13.20% to 20.90%); that is, 17.20% of the risk of having offspring with CHDs in the maternal diabetes group was attributed to any maternal diabetes.The population-attributable risk of any Figure 1.Association Between Maternal Factors and Isolated Congenital Heart Defects (CHDs) (18.5-24.9)andno diabetes were used as reference groups in logistic regression analysis.Statistical significance was reached with P < .05.GD indicates gestational diabetes; OR, odds ratio; T1D, type 1 diabetes; T2D, type 2 diabetes.diabetes 2. Association Between Maternal Factors and Congenital Heart Defect (CHD) Subgroups 3. Association Between Maternal Factors and Congenital Heart Disease (CHD) Subgroups in Multivariable Analysis

Table 2 .
Risk of Isolated CHD by Maternal Risk Factor Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CHD, congenital heart defect; GD, gestational diabetes; PAR, population-attributable risk; T1D, type 1 diabetes; T2D, type 2 diabetes.
7,16-19 Indeed, analyses of CHD subtypes were limited by low prevalence of individual malformations, even in large cohorts.A 2019 meta-analysis 20 of 19 studies with 2 416 546 participants reported pooled relative risks of having infants with CHDs of 1.08 (95% CI, 1.03-1.13) in mothers with overweight and 1.23 (95% CI, 1.17-1.29) in mothers with obesity.Nonetheless, most included studies were case-control studies, and few adjusted for confounding factors, such as maternal age, smoking, education, or diabetes.Moreover, many studies used BMI based on retrospective, self-reported data, which are subject to recall bias.

JAMA Network Open | Pediatrics 44.
Grossfeld P, Nie S, Lin L, Wang L, Anderson RH.Hypoplastic left heart syndrome: a new paradigm for an old disease?J Cardiovasc Dev Dis.2019;6(1):10.doi:10.3390/jcdd601001045.Wahabi HA, Alzeidan RA, Esmaeil SA.Pre-pregnancy care for women with pre-gestational diabetes mellitus: a systematic review and meta-analysis.BMC Public Health.2012;12(1):792.doi:10.1186/1471-2458-12-792Diagnoses Used in Excluding Individuals With Extracardiac Anomalies eTable 2. Congenital Heart Defect Subgroup Categories Were Classified According to Atlanta ICD-9 Classification eTable 3. ICD-9 Codes and Special Reimbursement Codes Used in Definition of Maternal Diabetes From Registries eTable 4. Prevalence of Congenital Heart Defects in Study Population eTable 5. Presence of Maternal Gestational Diabetes and No Diabetes by Body Mass Index in Mothers of Children With and Without Isolated Congenital Heart Defects eTable 6.Comparison Between Individuals With Missing and Nonmissing Data and Isolated Congenital Heart Defects eFigure 1. Flowchart of Selection of Study Participants eFigure 2. Prevalence of Maternal Diabetes During Study Period eFigure 3. Prevalence of Maternal Obesity and Congenital Heart Defects During Study Period eFigure 4. Association of Maternal Body Mass Index and Diabetes With All Congenital Heart Defect Subgroups eFigure 5. Association of Maternal Body Mass Index and Diabetes With All Congenital Heart Defect Subgroups Using Multivariable Logistic Regression Analysis